Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 06:26 UTC

pyfa-org / Pyfa

Python fitting assistant, cross-platform fitting tool for EVE Online

PythonGPL-3.0★ 1,770 stars⑂ 453 forkssince Jun 2013View on GitHub ↗
#eve-online#python#pyfa#mmo#fitting#wxpython

pyfa-org/Pyfa holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Community & Adoption (82/100) and lowest on AI Readiness (29/100). It was last updated 9 days ago. 2 contributors account for most of its recent work.

78
overall / 100
Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

78
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

pyfa-orgOrganization
33 followers6 public repossince Jan 2016

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

81Excellent · 21% of overall

Development activity

75Good
How it's scored
28.8/36Push recency — last push 9 days ago
18/36Commit cadence — 26/52 weeks with commits
18/18Commit volume — 166 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year166
human_commit_share—
days_since_last_push9
active_weeks_last_year26

Release discipline

90Excellent
How it's scored
27/27Ships releases — 100 releases published
36/36Release recency — latest release 9 days ago
27/27Release cadence — a release every ~19.7 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count100
latest_release_tagv2.68.0
releases_from_tagsno
days_since_latest_release9
mean_days_between_releases19.7

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

82Excellent · 17% of overall

Popularity & adoption

86Excellent
How it's scored
52.7/60Stars — 1,770 stars
22.1/25Forks — 453 forks
10.8/15Watchers — 90 watchers
Inputs used
forks453
stars1,770
watchers90
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

78Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (GPL-3.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
7.2/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges—
has_contributingyes
has_issue_templateyes
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

68Good · 23% of overall

Maintainer resilience (bus factor)

63Moderate
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
14.3/22.5Commit distribution — top contributor authored 36% of commits
13.5/13.5Contributor breadth — 100 contributors
10/10OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled100
top_contributor_share0.363

Issue & PR responsiveness

69Good
How it's scored
34.6/42Issue resolution — 82% of issues closed
23.7/30PR acceptance — 520/658 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
1.5/15OpenSSF Scorecard: Code-Review — Found 4/23 approved changesets -- score normalized to 1
Inputs used
merged_prs520
open_issues368
closed_issues1,740
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.825
closed_unmerged_prs138
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

74Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
11/25Owner reach — 33 followers of pyfa-org
18.2/25Track record — 6 public repos, account ~10 yr old
Inputs used
followers33
owner_typeOrganization
is_verified—
owner_loginpyfa-org
public_repos6
account_age_days3,844
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

66Good · 19% of overall

Engineering practices

54Moderate
How it's scored
0/24CI workflows
24/24Tests present
16/16Linter config — tox.ini
0/9.6Pre-commit hooks
0/6.4.editorconfig
14/20OpenSSF Scorecard: CI-Tests — 3 out of 4 merged PRs checked by a CI test -- score normalized to 7
Inputs used
has_cino
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics — 6 topics
10/10Wiki
Inputs used
topicseve-online, python, pyfa, mmo, fitting, wxpython
has_wikiyes
homepage—
docs_site—
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

40Weak · 16% of overall

Security posture

40Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
1.8/2.5CI-Tests — 3 out of 4 merged PRs checked by a CI test -- score normalized to 7
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-Review — Found 4/23 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 10 contributing companies or organizations
0/10Dangerous-Workflow — no data
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — no data
0/7.5Vulnerabilities — 12 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated14
scorecard_versionv5.5.0
checks_inconclusive4
scorecard_aggregate4
Excluded from scoring (no data or not applicable): Branch-Protection, Dangerous-Workflow, Packaging, Token-Permissions. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

29At Risk · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

40Weak
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — tox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
54.8/55Manageable file sizes — 3/693 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes1,380,536
source_files_sampled693
oversized_source_files3

Key facts

1,770GitHub stars
100contributors
166commits, last 12 months
9days since last push
100releases
2bus factor
368open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.0 / 10
4.0aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-07-17 06:26 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
7CI-Tests3 out of 4 merged PRs checked by a CI test -- score normalized to 7
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 4/23 approved changesets -- score normalized to 1
10Contributorsproject has 10 contributing companies or organizations
n/aDangerous-Workflowno workflows found
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 18 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
n/aToken-PermissionsNo tokens found
0Vulnerabilities12 existing vulnerabilities detected
All dependencies 28

Full resolved dependency set from the GitHub dependency graph: 0 direct and 28 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbeautifulsoup4—indirect
PyPIbeautifulsoup44.12.2indirect
PyPIcryptography—indirect
PyPIcryptography42.0.4indirect
PyPIdiskcache—indirect
PyPIlogbook—indirect
PyPIlogbook1.7.0.post0indirect
PyPImarkdown2—indirect
PyPImarkdown22.4.11indirect
PyPImatplotlib—indirect
PyPImatplotlib3.8.2indirect
PyPInumpy1.26.2indirect
PyPIpackaging—indirect
PyPIpackaging23.2indirect
PyPIpython-dateutil—indirect
PyPIpython-dateutil2.8.2indirect
PyPIpython-jose3.3.0indirect
PyPIpyyaml—indirect
PyPIpyyaml6.0.1indirect
PyPIrequests—indirect
PyPIrequests2.31.0indirect
PyPIrequests-cache1.1.1indirect
PyPIroman—indirect
PyPIroman4.1indirect
PyPIsqlalchemy—indirect
PyPIsqlalchemy1.4.50indirect
PyPIwxpython4.0.0b2indirect
PyPIwxpython4.2.1indirect
Raw JSON report machine-readable

Feedback

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.11.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics.